This Professor Says We've Been Looking At The Coronavirus Data Wrong
Yaneer Bar-Yam giving a talk.
An Interview with Yaneer Bar-Yam, Professor and President of New England Complex Systems Institute
Even as data science becomes ubiquitous, we still have a shortage of people who truly understand data. Yaneer Bar-Yam is a Professor and President of the New England Complex Systems Institute. He graduated from MIT and is an expert in complex systems. Throughout this pandemic, he has been meticulously analyzing COVID-19 data using both simple statistical models and complex system models and following government policies from all over the world. He wrote more than a few blog posts on his website to try to validate policy responses and to urge policymakers to consider how they are using data in their decision-making process.
What he sees are some common mistakes that we can avoid when analyzing our data. These are pervasive mistakes that people often make in different industries and in different research areas. As scientists, technologists, and policymakers, it’s possible to vastly improve our day-to-day judgments by side-stepping these mistakes.
Yaneer says, “If you want to use science for policy, you have to check the assumptions. In this case, it’s imperative to check the assumptions. It’s a responsibility.”
The Stakes Are High
There’s a difference between doing science and setting policy. Politicians and business leaders are setting policy. These policies affect lives. The stakes are much higher when lives are involved.
During this pandemic, globally, according to the World Health Organization, we already have over 3 million sick individuals and lost 200K+ lives. Some countries’ policies prevented the community spread of the disease. However, other countries’ policies were not enough.
Yaneer says, “There are always scientific assumptions made in scientific papers. Policy-makers have to know how to check those assumptions made and learn to evaluate the findings in light of those assumptions.”
Your Choice of Models, Variables, and More
At the same time, in epidemiology, social science, and economics, statistical models are used widely for analysis. These models are adequate to find answers to certain questions. But, to model our world taking account of changes that may occur, we need more sophisticated models. In physics, there’s the notion of modeling complex systems that Professor Yaneer has been using in his decades of research.
Yaneer says, “Why do we need the science of complex systems? If there are dependencies in the systems, then statistics don’t work. Standard calculus can’t describe things properly when there are abrupt large scale changes that involve changes in what many individuals are doing.”
No matter what models you use, you are selecting a group of variables that will give you the best picture of the answers that you seek. Depending on the data, with the right variables, you will gain the answers you are looking for. But, with the wrong variables, you can be drastically misled.
Yaneer says, “Often, it’s not the math that is wrong. It’s the variables that are wrong. You need to figure out what the right variables are. When people write down models, there’s a perspective that you have to include all the details. That’s not the case. It’s not possible to include everything. So you may miss something important. At the same time, most of the details are not important.”
There are techniques in physics such as Renormalization Group that will enable you to identify the relevant variables. Then, you can validate your model.
Yaneer says, “If you did your analysis wrong, then your model won’t fit the data. We need to clarify what we need to pay attention to. Then, you can figure out what the interventions can be.”
In the past decade, we’ve built models in epidemiology, social sciences, and economics that are largely based on statistical frameworks. These models are using data from past events to predict future events.
The use of statistical models has a hundred-year history and scientific fields haven’t caught up to the advances in mathematical methods of complex systems science. They are not taught in most universities. Even the new AI methods are mostly based on statistical assumptions. New big data sources help but only if the modeling assumptions are changed.
There are many modeling techniques, from more classic differential equations to agent-based models. However, only if they use the right variables will they get the right answers.
We haven’t had coronavirus outbreaks globally before this outbreak. We don’t have past data to go on. During this pandemic, agents within the system: a business, a person, a family, a community, their behaviors change. Through these behavioral changes and interactions with one another inside this complex system, events occur. This points to the need of using complex system models that focus on the most important information in our analysis.
Yaneer says, “It’s not about the sophistication of the math. It’s really about the right variables. You can find a simple model. Sometimes you just need a simple model. Ask: Can that model answer the question that we want to know?”
The Way You Think About The Problem Is Important
When you think about the pandemic, its effect on people’s lives, its effect on societies, and healthcare systems, you quickly realize that you will need to adapt a complex system framework rather than a statistical framework, especially when it comes to policy.
Often, each community has different characteristics. For instance, in large cities, you have more density in your community, in rural areas, you have less contact between people, but you may also have more frequent gatherings of church groups. These characteristics will determine the rate of transmission within the community. Once a community spread occurs, it is difficult to stop.
Refer to the graph above, Greece acted two weeks earlier than Spain and their numbers of cases were of order 100X fewer. They are now almost at zero and can safely open up their economy. Over a dozen countries that acted strongly, consistent with Yaneer’s recommendations, are now ready to go back to normal. He calls them the “Winners”. And hopes more will take these actions.
The reason that these countries were successful in stopping community spread is because they engaged people to quickly change their behaviors. Refer to the above graph, countries such as Vietnam, South Korea, New Zealand, etc.., all the countries in blue, are countries that were successful in stopping community spread.
In contrast, the U.S., United Kingdom, Sweden are countries that are dealing with community spread due to acting too late.
Academic scientists often think that behavioral changes are not possible, especially in a short time frame. But, when the stakes are high, not only are behavioral changes possible, these individual behavior changes impact the outcome of the pandemic drastically on a society as a whole.
Recommendations for Citizens
We are not nearly at the end of the pandemic even though some communities are choosing to open back up. It’s a good time to review the policies that came out of the data we’ve collected since the beginning of the pandemic.
Notably, in some countries with community spread, ordinary citizens are making their own judgments. That is reassuring. Our democratic process allows us the freedom of choice. That choice has to be exercised to protect ourselves and not to put us in further danger.
Yaneer says, “Coronavirus is a terrible disease. As a result, we don’t want it. When you get it, you can get really sick. It spreads fast through the community. No matter what society you live in, the multiplication rate for the infection is about 10x per week. When the rate grows exponentially, we quickly go from outbreak to pandemic. You don’t want community spread. If you take the right actions quickly, then you save your life and save people’s lives in your community by preventing community spread of the virus.”
Debunking a few myths:
Herd Immunity
Yaneer says, “Herd Immunity is scientism and not science. It’s the idea that we should just let the disease kill people.”
Scaling Population Size
Yaneer says, “When it comes to preventing the community spread of the disease, scaling the population does not matter. If you look at countries that have been successful in preventing community spread, it only takes 5 weeks to stop the spread if you take drastic actions such as: implementing contact tracing, travel restrictions, extensive testing, wearing masks and isolating people without infecting their families.”
These are a few of Dr. Yaneer’s recommendations for all of us. There are 9 points of “How to Win” listed on his website that you can visit for more details. You can read more at Stopping the Coronavirus Pandemic - A Community-based analysis.
Get everyone on board: All levels/aspects of government, communities, companies, individuals have to go all out to stop this disease.
Lockdown: Separate individuals to prevent transmission.
Isolation: Set up facilities for mild and moderate cases so they can’t infect their housemates or others. Screen door to door to find all cases.
Wear masks in shared spaces: Coughs, sneezes, breathing out all spread the virus.
Travel restrictions: These will stop new outbreaks from starting, make contact tracing feasible, and preserve local achievement for a ratchet effect—maintaining forward progress by preventing backward retreat.
Essential services should be safe: Companies providing essentials should develop and provide delivery, curbside pickup, or other methods to reduce the risk for employees and customers.
Testing, testing, testing: Try fighting something you can’t see. Tests may include genetic (PCR), CT scans, improved symptomatic screening, or others. By testing people in specific areas, we can identify those zones to focus on and those where we can relax restrictions.
Health guidelines: Focus on keeping people healthy to prevent mild cases from becoming severe.
Support medical care: Hospitals and healthcare workers are overwhelmed and this will get worse until our actions stop the transmission. Give them the tools they need to do the best they can to save lives
This article was written with special thanks to "Covid-19 Simulation Summit" organized by SingularityNET and DAIA (Decentralized AI Alliance)".